Probability and Statistics Questions and Answers – Poisson Distribution

This set of Probability and Statistics Multiple Choice Questions & Answers (MCQs) focuses on “Poisson Distribution”.

1. In a Poisson Distribution, if ‘n’ is the number of trials and ‘p’ is the probability of success, then the mean value is given by?
a) m = np
b) m = (np)2
c) m = np(1-p)
d) m = p
View Answer

Answer: a
Explanation: For a discrete probability function, the mean value or the expected value is given by
Mean(μ)=\(\sum_{x=0}^n xp(x)\)
For Poisson Distribution P(x)=\(\frac{e^{-m}m^x}{x!}\) substitute in above equation and solve to get µ = m = np.

2. If ‘m’ is the mean of a Poisson Distribution, then variance is given by ___________
a) m2
b) m12
c) m
d) m2
View Answer

Answer: c
Explanation: For a discrete probability function, the variance is given by
Variance (v) = \(\sum_{x=0}^n x^2p(x)-\mu^2\)

Where µ is the mean, substitute P(x)=\(\frac{e^{-m}m^x}{x!}\), in the above equation and put µ = m to obtain
V = m.

3. The p.d.f of Poisson Distribution is given by ___________
a) \(\frac{e^{-m}m^x}{x!}\)
b) \(\frac{e^{-m}x!}{m^x}\)
c) \(\frac{x!}{m^xe^{-m}}\)
d) \(\frac{e^m m^x}{x!}\)
View Answer

Answer: a
Explanation: This is a standard formula for Poisson Distribution, it needs no explanation.
Even though if you are interested to know the derivation in detail, you can refer to any of the books or source on internet that speaks of this matter.
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4. If ‘m’ is the mean of a Poisson Distribution, the standard deviation is given by ___________
a) \(\sqrt{m}\)
b) m2
c) m
d) m2
View Answer

Answer: a
Explanation: The variance of a Poisson distribution with mean ‘m’ is given by V = m, hence
Standard Deviation = \(\sqrt{variance} = \sqrt{m}\)

5. In a Poisson Distribution, the mean and variance are equal.
a) True
b) False
View Answer

Answer: a
Explanation: Mean = m
Variance = m
∴ Mean = Variance.
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6. In a Poisson Distribution, if mean (m) = e, then P(x) is given by ___________
a) \(\frac{e^{(x-m)}}{x!}\)
b) \(\frac{e^{(m-x)}}{x!}\)
c) \(\frac{x!}{e^{(m-x)}}\)
d) \(\frac{x!}{e^{(x-m)}}\)
View Answer

Answer: b
Explanation: P(x)=\(\frac{e^{-m}m^x}{x!}\)
Put m = e, and get correct solution.

7. Poisson distribution is applied for ___________
a) Continuous Random Variable
b) Discrete Random Variable
c) Irregular Random Variable
d) Uncertain Random Variable
View Answer

Answer: b
Explanation: Poisson Distribution along with Binomial Distribution is applied for Discrete Random variable. Speaking more precisely, Poisson Distribution is an extension of Binomial Distribution for larger values ‘n’. Since Binomial Distribution is of discrete nature, so is its extension Poisson Distribution.
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8. If ‘m’ is the mean of Poisson Distribution, the P(0) is given by ___________
a) e-m
b) em
c) e
d) m-e
View Answer

Answer: a
Explanation: P(x)=\(\frac{e^{-m}m^x}{x!}\)
Put x = 0, to obtain e-m.

9. In a Poisson distribution, the mean and standard deviation are equal.
a) True
b) False
View Answer

Answer: b
Explanation: In a Poisson Distribution,
Mean = m
Standard Deivation = m12
∴ Mean and Standard deviation are not equal.
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10. For a Poisson Distribution, if mean(m) = 1, then P(1) is?
a) 1/e
b) e
c) e/2
d) Indeterminate
View Answer

Answer: a
Explanation: P(x)=\(\frac{e^{-m}m^x}{x!}\)
Put m = x = 1, (given) to obtain 1/e.

11. The recurrence relation between P(x) and P(x +1) in a Poisson distribution is given by ___________
a) P(x+1) – m P(x) = 0
b) m P(x+1) – P(x) = 0
c) (x+1) P(x+1) – m P(x) = 0
d) (x+1) P(x) – x P(x+1) = 0
View Answer

Answer: c
Explanation: P(x)=\(\frac{e^{-m}m^x}{x!}\)
p(x+1) = e-1 mx+1 /(x + 1)!
Divide P(x+1) by P(x) and rearrange to obtain (x+1) P(x+1) – m P(x) = 0.

Sanfoundry Global Education & Learning Series – Probability and Statistics.

To practice all areas of Probability and Statistics, here is complete set of 1000+ Multiple Choice Questions and Answers.

If you find a mistake in question / option / answer, kindly take a screenshot and email to [email protected]

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Manish Bhojasia, a technology veteran with 20+ years @ Cisco & Wipro, is Founder and CTO at Sanfoundry. He lives in Bangalore, and focuses on development of Linux Kernel, SAN Technologies, Advanced C, Data Structures & Alogrithms. Stay connected with him at LinkedIn.

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